Step-by-step tutorials on building voice and chat AI agents using OpenAI Agents SDK, Realtime API, function calling, multi-agent orchestration, and production deployment patterns.
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Explore how the Vercel AI SDK's generativeUI capability lets AI agents stream fully interactive React components to users, replacing static text responses with dynamic, data-rich interfaces.
Build an AI agent that reads documents, extracts named entities and their relationships, constructs a knowledge graph stored in Neo4j, and provides a natural language query interface over the graph.
Build a visual question answering agent that understands images, routes questions to specialized analysis modules, performs multi-modal reasoning, and generates accurate natural language answers about any image content.
Build an AI agent pipeline for handwriting recognition that processes handwritten forms and notes, extracts field values with confidence scoring, and routes low-confidence results to human reviewers for correction.
Master the architecture of streaming AI agents that deliver token-by-token output while interleaving tool calls, using Server-Sent Events and progressive rendering to create responsive user experiences.
Discover how to build AI agents that can write new Python tools at runtime, validate them in a sandbox, register them dynamically, and use them in subsequent reasoning — creating truly self-extending agent systems.
Build a vision AI pipeline that scans receipts and invoices, extracts vendor names, dates, line items, and totals, categorizes expenses, and integrates with accounting systems for fully automated expense processing.
Learn how to build an end-to-end document intelligence agent that combines Tesseract OCR, layout detection, zone classification, and structured information extraction to process any document type automatically.
